Operating policies in multi-warehouse drone delivery systems

Abstract

Drones are increasingly used to deliver packages with high efficiency in several areas. We study a multi-warehouse drone delivery system, considering the allocation rule that all warehouses share the drones and the allocation rule that each warehouse owns its drones. Both plug-in charge and battery swap strategies are investigated for battery management. We examine the random and closest drone to warehouse assignment rules, and design a heuristic to improve the drone to warehouse assignment rule. A closed queueing network is built to estimate the maximum throughput capacity and a cost minimisation model is developed for cost analysis. We validate the analytical model by simulation and conduct numerical experiments to analyse the operating polices. The results show that the closest drone to warehouse assignment rule outperforms the random drone to warehouse assignment rule when the number of drones is not large, and our heuristic can improve the throughput capacity by about 13.31%. The battery swap strategy provides a better throughput capacity than the plug-in charge strategy in most cases, while it needs more investment. Moreover, the shared allocation rule gives a larger throughput capacity than the dedicated allocation rule, and it reduces the operating cost by about 30.70%.

Keywords:

• logistics
• drone delivery system
• performance analysis
• queueing networks

Acknowledgments

This research is partially supported by the National Natural Science Foundation of China (grant number 71801225), (grant number 71620107002), (grant number 71971095), (grant number 71821001) and Hubei Provincial Natural Science Foundation of China (grant number 2018CFB160).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research is partially supported by the National Natural Science Foundation of China [Grant Numbers 71801225, 71620107002, 71971095, and 71821001] and Natural Science Foundation of Hubei Province of China [Grant Number 2018CFB160].